Triple
T30731052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military flags of Spain |
E782423
|
entity |
| Predicate | standardRatio |
P180808
|
FINISHED |
| Object | 2:3 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 2:3 | Statement: [Military flags of Spain, standardRatio, 2:3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardRatio Context triple: [Military flags of Spain, standardRatio, 2:3]
-
A.
sideRatioLength
Indicates the proportional relationship between the lengths of two or more sides in a geometric figure.
-
B.
alternativeRatio
Indicates the proportion or comparative share between different alternative options within a given context.
-
C.
representationRatio
Indicates the proportional relationship between how much one entity represents, depicts, or stands in for another relative to some whole or reference amount.
-
D.
standardPar
Indicates that two entities are parallel and conform to a recognized or defined standard of parallelism.
-
E.
radiusRatio
Indicates the proportional relationship between one radius and another, typically expressing how large one is relative to the other.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224ad9f9c81908e02a79ae0001137 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
| PDg | Predicate description generation | batch_69f7516c538481908c6e55cf76add098 |
completed | May 3, 2026, 1:45 p.m. |
Created at: April 29, 2026, 8:37 p.m.